Iterative Semi-Global Matching for Robust Driver Assistance Systems

  • Simon Hermann
  • Reinhard Klette
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7726)


Semi-global matching (SGM) is a technique of choice for dense stereo estimation in current industrial driver-assistance systems due to its real-time processing capability and its convincing performance. In this paper we introduce iSGM as a new cost integration concept for semi-global matching. In iSGM, accumulated costs are iteratively evaluated and intermediate disparity results serve as input to generate semi-global distance maps. This novel data structure supports fast analysis of spatial disparity information and allows for reliable search space reduction in consecutive cost accumulation. As a consequence horizontal costs are stabilized which improves the robustness of the matching result. We demonstrate the superiority of this iterative integration concept against a standard configuration of semi-global matching and compare our results to current state-of-the-art methods on the KITTI Vision Benchmark Suite.


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© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Simon Hermann
    • 1
  • Reinhard Klette
    • 1
  1. 1.The .enpeda.. Project, Department of Computer ScienceThe University of AucklandNew Zealand

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